Upload PPO LunarLander-v2 trained agent
Browse files- README.md +37 -0
- config.json +1 -0
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +96 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/system_info.txt +7 -0
- replay.mp4 +0 -0
- results.json +1 -0
README.md
ADDED
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: stable-baselines3
|
3 |
+
tags:
|
4 |
+
- LunarLander-v2
|
5 |
+
- deep-reinforcement-learning
|
6 |
+
- reinforcement-learning
|
7 |
+
- stable-baselines3
|
8 |
+
model-index:
|
9 |
+
- name: PPO
|
10 |
+
results:
|
11 |
+
- task:
|
12 |
+
type: reinforcement-learning
|
13 |
+
name: reinforcement-learning
|
14 |
+
dataset:
|
15 |
+
name: LunarLander-v2
|
16 |
+
type: LunarLander-v2
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: 236.99 +/- 69.79
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **PPO** Agent playing **LunarLander-v2**
|
25 |
+
This is a trained model of a **PPO** agent playing **LunarLander-v2**
|
26 |
+
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
|
27 |
+
|
28 |
+
## Usage (with Stable-baselines3)
|
29 |
+
TODO: Add your code
|
30 |
+
|
31 |
+
|
32 |
+
```python
|
33 |
+
from stable_baselines3 import ...
|
34 |
+
from huggingface_sb3 import load_from_hub
|
35 |
+
|
36 |
+
...
|
37 |
+
```
|
config.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n Policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7f678e1678b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f678e167940>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f678e1679d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f678e167a60>", "_build": "<function ActorCriticPolicy._build at 0x7f678e167af0>", "forward": "<function ActorCriticPolicy.forward at 0x7f678e167b80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f678e167c10>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f678e167ca0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f678e167d30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f678e167dc0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f678e167e50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f678e167ee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f678e169dc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681457387841793977, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAFbgf75COEU+J/kGPtfcgb6rPqC8u9lovAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3908, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "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", "n": 4, "_shape": [], "dtype": "int64", "_np_random": "RandomState(MT19937)"}, "n_envs": 1, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2d6f0ea6cdab23564e91e4d1aee91fb92ac539a44d091574203564d2f72348a3
|
3 |
+
size 150379
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.8.0
|
ppo-LunarLander-v2/data
ADDED
@@ -0,0 +1,96 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"policy_class": {
|
3 |
+
":type:": "<class 'abc.ABCMeta'>",
|
4 |
+
":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
|
5 |
+
"__module__": "stable_baselines3.common.policies",
|
6 |
+
"__doc__": "\n Policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ",
|
7 |
+
"__init__": "<function ActorCriticPolicy.__init__ at 0x7f678e1678b0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f678e167940>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f678e1679d0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f678e167a60>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f678e167af0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f678e167b80>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f678e167c10>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f678e167ca0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f678e167d30>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f678e167dc0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f678e167e50>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f678e167ee0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f678e169dc0>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1000448,
|
25 |
+
"_total_timesteps": 1000000,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1681457387841793977,
|
30 |
+
"learning_rate": 0.0003,
|
31 |
+
"tensorboard_log": null,
|
32 |
+
"lr_schedule": {
|
33 |
+
":type:": "<class 'function'>",
|
34 |
+
":serialized:": "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"
|
35 |
+
},
|
36 |
+
"_last_obs": {
|
37 |
+
":type:": "<class 'numpy.ndarray'>",
|
38 |
+
":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAFbgf75COEU+J/kGPtfcgb6rPqC8u9lovAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
|
39 |
+
},
|
40 |
+
"_last_episode_starts": {
|
41 |
+
":type:": "<class 'numpy.ndarray'>",
|
42 |
+
":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
|
43 |
+
},
|
44 |
+
"_last_original_obs": null,
|
45 |
+
"_episode_num": 0,
|
46 |
+
"use_sde": false,
|
47 |
+
"sde_sample_freq": -1,
|
48 |
+
"_current_progress_remaining": -0.00044800000000000395,
|
49 |
+
"_stats_window_size": 100,
|
50 |
+
"ep_info_buffer": {
|
51 |
+
":type:": "<class 'collections.deque'>",
|
52 |
+
":serialized:": "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"
|
53 |
+
},
|
54 |
+
"ep_success_buffer": {
|
55 |
+
":type:": "<class 'collections.deque'>",
|
56 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
57 |
+
},
|
58 |
+
"_n_updates": 3908,
|
59 |
+
"observation_space": {
|
60 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
61 |
+
":serialized:": "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",
|
62 |
+
"dtype": "float32",
|
63 |
+
"_shape": [
|
64 |
+
8
|
65 |
+
],
|
66 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
67 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
68 |
+
"bounded_below": "[False False False False False False False False]",
|
69 |
+
"bounded_above": "[False False False False False False False False]",
|
70 |
+
"_np_random": null
|
71 |
+
},
|
72 |
+
"action_space": {
|
73 |
+
":type:": "<class 'gym.spaces.discrete.Discrete'>",
|
74 |
+
":serialized:": "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",
|
75 |
+
"n": 4,
|
76 |
+
"_shape": [],
|
77 |
+
"dtype": "int64",
|
78 |
+
"_np_random": "RandomState(MT19937)"
|
79 |
+
},
|
80 |
+
"n_envs": 1,
|
81 |
+
"n_steps": 1024,
|
82 |
+
"gamma": 0.999,
|
83 |
+
"gae_lambda": 0.98,
|
84 |
+
"ent_coef": 0.01,
|
85 |
+
"vf_coef": 0.5,
|
86 |
+
"max_grad_norm": 0.5,
|
87 |
+
"batch_size": 64,
|
88 |
+
"n_epochs": 4,
|
89 |
+
"clip_range": {
|
90 |
+
":type:": "<class 'function'>",
|
91 |
+
":serialized:": "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"
|
92 |
+
},
|
93 |
+
"clip_range_vf": null,
|
94 |
+
"normalize_advantage": true,
|
95 |
+
"target_kl": null
|
96 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0351d2547e5f47fa02a75b618d694c89554c17700eb9f437c86fdb24a2873050
|
3 |
+
size 87929
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6a272e9fb91601b3b9e03f47b78f57cd3b5e011429933fd5978463e2ba0e337f
|
3 |
+
size 43329
|
ppo-LunarLander-v2/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
ppo-LunarLander-v2/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
|
2 |
+
- Python: 3.9.16
|
3 |
+
- Stable-Baselines3: 1.8.0
|
4 |
+
- PyTorch: 2.0.0+cu118
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.22.4
|
7 |
+
- Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (235 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 236.99125085976, "std_reward": 69.79303828510803, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-14T08:19:23.091090"}
|